Matches in SemOpenAlex for { <https://semopenalex.org/work/W4310648296> ?p ?o ?g. }
Showing items 1 to 92 of
92
with 100 items per page.
- W4310648296 abstract "Event sequence, asynchronously generated with random timestamp, is ubiquitous among applications. The precise and arbitrary timestamp can carry important clues about the underlying dynamics, and has lent the event data fundamentally different from the time-series whereby series is indexed with fixed and equal time interval. One expressive mathematical tool for modeling event is point process. The intensity functions of many point processes involve two components: the background and the effect by the history. Due to its inherent spontaneousness, the background can be treated as a time series while the other need to handle the history events. In this paper, we model the background by a Recurrent Neural Network (RNN) with its units aligned with time series indexes while the history effect is modeled by another RNN whose units are aligned with asynchronous events to capture the long-range dynamics. The whole model with event type and timestamp prediction output layers can be trained end-to-end. Our approach takes an RNN perspective to point process, and models its background and history effect. For utility, our method allows a black-box treatment for modeling the intensity which is often a pre-defined parametric form in point processes. Meanwhile end-to-end training opens the venue for reusing existing rich techniques in deep network for point process modeling. We apply our model to the predictive maintenance problem using a log dataset by more than 1000 ATMs from a global bank headquartered in North America." @default.
- W4310648296 created "2022-12-14" @default.
- W4310648296 creator A5007695606 @default.
- W4310648296 creator A5019708391 @default.
- W4310648296 creator A5034826329 @default.
- W4310648296 creator A5046703129 @default.
- W4310648296 creator A5087158377 @default.
- W4310648296 date "2017-05-24" @default.
- W4310648296 modified "2023-09-27" @default.
- W4310648296 title "Modeling The Intensity Function Of Point Process Via Recurrent Neural Networks" @default.
- W4310648296 doi "https://doi.org/10.48550/arxiv.1705.08982" @default.
- W4310648296 hasPublicationYear "2017" @default.
- W4310648296 type Work @default.
- W4310648296 citedByCount "0" @default.
- W4310648296 crossrefType "posted-content" @default.
- W4310648296 hasAuthorship W4310648296A5007695606 @default.
- W4310648296 hasAuthorship W4310648296A5019708391 @default.
- W4310648296 hasAuthorship W4310648296A5034826329 @default.
- W4310648296 hasAuthorship W4310648296A5046703129 @default.
- W4310648296 hasAuthorship W4310648296A5087158377 @default.
- W4310648296 hasBestOaLocation W43106482961 @default.
- W4310648296 hasConcept C105795698 @default.
- W4310648296 hasConcept C111919701 @default.
- W4310648296 hasConcept C113954288 @default.
- W4310648296 hasConcept C11413529 @default.
- W4310648296 hasConcept C114614502 @default.
- W4310648296 hasConcept C117251300 @default.
- W4310648296 hasConcept C119857082 @default.
- W4310648296 hasConcept C121332964 @default.
- W4310648296 hasConcept C14036430 @default.
- W4310648296 hasConcept C143724316 @default.
- W4310648296 hasConcept C147168706 @default.
- W4310648296 hasConcept C151319957 @default.
- W4310648296 hasConcept C151730666 @default.
- W4310648296 hasConcept C154945302 @default.
- W4310648296 hasConcept C2778067643 @default.
- W4310648296 hasConcept C2779662365 @default.
- W4310648296 hasConcept C31258907 @default.
- W4310648296 hasConcept C33923547 @default.
- W4310648296 hasConcept C41008148 @default.
- W4310648296 hasConcept C50644808 @default.
- W4310648296 hasConcept C62520636 @default.
- W4310648296 hasConcept C774472 @default.
- W4310648296 hasConcept C78458016 @default.
- W4310648296 hasConcept C79403827 @default.
- W4310648296 hasConcept C86803240 @default.
- W4310648296 hasConcept C88871306 @default.
- W4310648296 hasConcept C98045186 @default.
- W4310648296 hasConceptScore W4310648296C105795698 @default.
- W4310648296 hasConceptScore W4310648296C111919701 @default.
- W4310648296 hasConceptScore W4310648296C113954288 @default.
- W4310648296 hasConceptScore W4310648296C11413529 @default.
- W4310648296 hasConceptScore W4310648296C114614502 @default.
- W4310648296 hasConceptScore W4310648296C117251300 @default.
- W4310648296 hasConceptScore W4310648296C119857082 @default.
- W4310648296 hasConceptScore W4310648296C121332964 @default.
- W4310648296 hasConceptScore W4310648296C14036430 @default.
- W4310648296 hasConceptScore W4310648296C143724316 @default.
- W4310648296 hasConceptScore W4310648296C147168706 @default.
- W4310648296 hasConceptScore W4310648296C151319957 @default.
- W4310648296 hasConceptScore W4310648296C151730666 @default.
- W4310648296 hasConceptScore W4310648296C154945302 @default.
- W4310648296 hasConceptScore W4310648296C2778067643 @default.
- W4310648296 hasConceptScore W4310648296C2779662365 @default.
- W4310648296 hasConceptScore W4310648296C31258907 @default.
- W4310648296 hasConceptScore W4310648296C33923547 @default.
- W4310648296 hasConceptScore W4310648296C41008148 @default.
- W4310648296 hasConceptScore W4310648296C50644808 @default.
- W4310648296 hasConceptScore W4310648296C62520636 @default.
- W4310648296 hasConceptScore W4310648296C774472 @default.
- W4310648296 hasConceptScore W4310648296C78458016 @default.
- W4310648296 hasConceptScore W4310648296C79403827 @default.
- W4310648296 hasConceptScore W4310648296C86803240 @default.
- W4310648296 hasConceptScore W4310648296C88871306 @default.
- W4310648296 hasConceptScore W4310648296C98045186 @default.
- W4310648296 hasLocation W43106482961 @default.
- W4310648296 hasLocation W43106482962 @default.
- W4310648296 hasOpenAccess W4310648296 @default.
- W4310648296 hasPrimaryLocation W43106482961 @default.
- W4310648296 hasRelatedWork W2315252188 @default.
- W4310648296 hasRelatedWork W2605191235 @default.
- W4310648296 hasRelatedWork W2944826853 @default.
- W4310648296 hasRelatedWork W2963022764 @default.
- W4310648296 hasRelatedWork W4255748661 @default.
- W4310648296 hasRelatedWork W4281386417 @default.
- W4310648296 hasRelatedWork W4308013158 @default.
- W4310648296 hasRelatedWork W4310648296 @default.
- W4310648296 hasRelatedWork W4311438958 @default.
- W4310648296 hasRelatedWork W4327831767 @default.
- W4310648296 isParatext "false" @default.
- W4310648296 isRetracted "false" @default.
- W4310648296 workType "article" @default.